This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. A switch to anaerobic metabolism and a resultant local increase in lactate is noted in the malignant progression of most cancers. The associated increase in glucose uptake to compensate for the inefficient anaerobic metabolism is the basis for detection of tumor metastasis by 2-flouorodeoxyglucose positron emission tomography (FDG-PET). It is hoped that improvements in the MRI detection of lactate will give the same information as FDG-PET without the need for radioactive tracers. Currently, two challenges stand in the way of MRI detection of lactate, the low signal produced from lactate and the difficulties in separating fat signal from lactate signal. The selective multiple quantum coherence (Sel-MQC) technique offers several advantages over other sequences. Without going into technical detail, this sequence offers promise for the clinical detection of lactate by full separation of fat and lactate signals as well as optimization of lactate signal strength. While single slice versions and very recently a 3-dimensional version of this technique have been used for small animals, rarely is lactate editing realized on clinical scanners. To the goal of clinical utilization of MRI detection of lactate for tumor detection, we have recently demonstrated 3D Sel-MQC lactate imaging with clinical hardware. This research is currently being applied to the detection of lactate in a variety of pathologic/physiologic conditions in vivo.